Özet:

In the current research, the importance of maize seed identification and its varieties are appropriately studied. The machine vision was used to quickly employ methods for checking the seed quality, which helps for better yield. The proposed methods central aspect helps integrate the machine vision with ML methods to analyse different parameters such as color, shape, and texture. Typically, ML techniques are used to capture the various details such as seed quality, pruning, fertilizer application, and environmental and genetic analysis to increase the yield of maize in agriculture. Eventually, it is important to find an effective integration of ML methods in the identification of maize seeds in the agriculture field, which helps the farmers to procure better yield and minimize the loss. Healthy maize seeds are essential for better yield, and various detection methods are utilized in research to find the best one in agriculture. However, most of the techniques are manual, expensive, and timeconsuming, which makes the process difficult. The proposed techniques that have been utilized in the study have the possibility to present accurate results that help in identifying similar maize varieties. Therefore, different parameters are used in the process in order to identify the maize seeds and their varieties to procure efficient results compared to the existing techniques.

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